Neural network sensitivity analysis of the detected signal from an SO2 electrode

Mei-Jywan Syu, Jwo Ying Liu

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

A novel SO2 electrode was made by doping polyaniline onto Nafion to detect SO2 at ppm level with a linear correlation between the response current and the SO2 concentration in the range of 20 to 250 ppm. By applying artificial neural network, it was possible to predict the SO2 concentration so that a shorter response time (3 min compared with 6 min) was achieved without the need of a noise filter. The operation conditions, cycles for acid/base treatment and immersion time, considered as the affecting factors of the polyaniline membrane treatment were used for the study of sensitivity analysis. Both the results analyzed from the transfer functions of 2/(1 + e-x) and sgn(x)·x2/(1 + x2) are presented. Prediction of the neural network for sensitivity analysis of the SO2 electrode signal was tested first. Then, the two operation variables considered as important factors affecting the properties of the membrane were studied in view of their influence toward the response current.

原文English
頁(從 - 到)1-8
頁數8
期刊Sensors and Actuators, B: Chemical
50
發行號1
DOIs
出版狀態Published - 1998 7月 15

All Science Journal Classification (ASJC) codes

  • 電子、光磁材料
  • 儀器
  • 凝聚態物理學
  • 表面、塗料和薄膜
  • 金屬和合金
  • 電氣與電子工程
  • 材料化學

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